Enhancing flow cytometry discrimination with geometric transformation

Abstract

In flow cytometry, particles ( 2 ) can be distinguished between populations ( 8 ) by combining n-dimensional parameter data, which may be derived from signal data from a particle, to mathematically achieve numerical results representative of an alteration ( 48 ). An alteration may include a rotational alteration, a scaled alteration, or perhaps even a translational alteration. Alterations may enhance separation of data points which may provide real-time classification ( 49 ) of signal data corresponding to individual particles into one of at least two populations.

We claim: 
     
       1. A flow cytometer comprising:
 a nozzle for entraining particles in a fluid stream; 
 laser focusing optics for focusing a laser beam onto an interrogation point on the fluid stream; 
 a first detector for producing a first signal affiliated with individual particles in the fluid stream; 
 a second detector for producing at least one additional signal affiliated with said individual particles in the fluid stream; and 
 one or more processors having computer readable memory and instructions written thereon to:
 detect a first signal from the first detector based on individual particles in the stream; 
 detect at least one additional signal from the second detector based on individual particles in the stream; 
 convert said first signal and said at least one additional signal affiliated with said individual particles into n-dimensional parameter data, where n is equal to the number of signals, wherein at least two populations of said individual particles overlap in one of said n-dimensions; 
 mathematically alter the n-dimensional parameter data by at least rotating the n-dimensional parameter data to increase the spatial separation in the dimension having the overlap; 
 real-time classifying said n-dimensional parameter data of each of said individual particles into one of said at least two populations using said rotated n-dimensional parameter data; and 
 discriminate between said individual particles based upon said real-time classification. 
 
 
     
     
       2. The flow cytometer of  claim 1 , wherein the second detector comprises a side detector. 
     
     
       3. The flow cytometer of  claim 1 , wherein the one or more processors having computer readable memory further comprises instructions written thereon for simultaneously processing said n-dimensional parameter data to mathematically achieve numerical results of said rotational alteration in addition to a scaled alteration and a translation alteration. 
     
     
       4. The flow cytometer of  claim 1 , wherein the one or more processors having computer readable memory further comprises instructions written thereon for generating a graphical representation of said at least two populations of said n-dimensional parameter data. 
     
     
       5. The flow cytometer of  claim 4 , wherein said graphical representation of said at least two populations of said n-dimensional parameter data comprises an n-parameter data plot in a Cartesian coordinate system. 
     
     
       6. The flow cytometer of  claim 1 , wherein said particles comprise sperm and wherein at least one of the two populations comprises an X-bearing sperm population or a Y-bearing sperm population.